This project is based on a final Project of the Lab Course: Image Reconstruction and Visualization using C++, at Technical University of Munich.
- Alex Gaul
- Simon Griebel
- Maximilian Hornung
- Dependencies
- How to run
- Acquistion widget manual
- Reconstruction widget manual
- Visualization widget manual
Our project depends on both Eigen3 and Qt5.
We use CMake (minimum version 3.5.1) to
manage our program's structure to simplify changes
in it, and
doxygen (>=1.8.0) for documentation.
The program can be executed typing
./part2
into a terminal (at the location of the executable, which is called part2 by default). After that, the UI starts and automatically loads a small 3D phantom.
Our project will automatically create its documentation during build - the documentation can be found in the docs/ directory inside of the build folder. The documentation can be generated manually by executing 'make doc' at the build folder's location).
To view the documentation open the html/index.html file inside of that directory (e.g. in Firefox).
In the acquisition widget, the user can see the position of X-ray emitter and detector (who form an acquisition pose together) from three all axes. Using the keyboard arrow keys, the acquisition pose can be rotated all around the volume, the position of emitter and detector are updated accordingly. The user can also show the rays between the emitter and the pixels of the detector.
The user can add and remove acquisition poses by clicking "store current pose" and "delete current pose". These poses are then used for reconstruction.
In experiments, we found out 30 circles of poses with 30 poses per circle (maximum) are sufficient to reconstruct all information of a 10x10x10 volume (using 40 iterations of CG).
It would be cumbersome to enter all these poses manually - therefore we made it possible to generate poses these poses automatically. The user has to provide the number of circles and the number of poses per circle only.
The user is also able to change the resolution and size of the detector, as well as its distance to the volume. This distance is not taken absolutely, but related to the size of the volume - because of that, similar values for the distance will result in similar behavior of the imaging setup. By including these configuration possibilities, many different imaging setups can be simulated without changing the software.
All positions of acquisition poses' emitters are shown on the screen, to convince the user of a regular sampling of the volume.
On the right side of the screen, the user can see the current acquisition data (the image that reaches the detector in the current acquisition pose). It is also possible to show all acquisitions in a linearized way.
The top part of this widget shows the reconstruction results. Each voxel is shown as a square area, therefore data is not blurred when the window size is changed.
To perform the reconstruction using Conjugate Gradient (CG) algorithm, press "Load Acquisition". This task is computationally expensive and can take several seconds. After the computations have finished, it is possible to scroll through the reconstructed volume (along all three axes, which can be chosen using a slider).
There are several possibilities of adjusting the reconstruction setup in the lower part of this widget:
- The number of iterations for CG can be changed - more iterations improve the results, but also increase the computational effort.
- The user has the possibility to add a custom amount of noise to the acquisition (to simulate the situation in real world scenarios).
- Regularization can be enabled to reduce the impact of noise on reconstruction results. The user has the possibilty to enter a custom value for lambda, to change the regularization parameter of the Tikhonov regularization. Warning: Too high values for lambda can degrade the reconstruction results to a level below the noisy image!
After changing the setup of reconstruction, the user has to hit "Update reconstruction" to apply his changes and recompute the reconstructed volume using the new setup.
Our visualization widget implements Multiplanar Reconstruction (MPR) and Direct Volume Rendering (DVR) using Maximum Intensity Projection (MIP).
Our implementation of MPR does not only support MPR from the origin, but the user can specify a custom origin point in 3D. Additionally, the user can change rotation around Y and Z axis as well as the zoom factor (e.g. to magnify interesting medical details).
The software supports both perspective and orthographic DVR. The user is able to adjust the rotation along Y and Z axis, as well as a custom zoom factor, step width and distance between camera and volume to be rendered.
- full screen mode
Acquisition:
- 3 axes view of Acquisition Poses
- Configuration of Acquisition Poses
- Widget to show all acquisitions
Reconstruction:
- Parallelization using OpenMP
- Scrolling trough reconstruction result along all three axes
Visualization:
- User defined Zoom for MPR
- Configuration of MPR
- Perspective DVR
- Configuration / zoom for DVR